Genetics of age-related macular degeneration
Bibliographic record
Abstract
PURPOSE OF REVIEW: Age-related macular degeneration (AMD) was until recently viewed as a part of the normal aging process; however, we are increasingly aware that genetic factors play a much greater role than previously suspected. This review will provide an up-to-date snapshot of the genetics of AMD to help guide our thoughts about its causes and the risk for family members. RECENT FINDINGS: Epidemiological research and basic bench research have identified pathways of oxidative stress, lipid metabolism and inflammation as playing causative roles in the pathogenesis of AMD. Emerging research is focusing on the biology of the retinal pigment epithelium as secreting pro and anti-inflammatory mediators in the eye. Antivascular endothelial growth factor therapy has dramatically improved the prognosis for neovascular or wet AMD patients. Nutritional supplementation with antioxidants and omega-3 fatty acids has provided treatment options for patients with atrophic or dry AMD. We should expect that some of the response to therapy might be genetically determined. SUMMARY: First-degree relatives of patients with AMD tend to have a higher risk of AMD. Recognizing an inherent genetic risk of AMD in these patients will improve their management and potentially help prevent blindness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".